International Journal of Scientific & Technology Research

IJSTR@Facebook IJSTR@Twitter IJSTR@Linkedin
Home About Us Scope Editorial Board Blog/Latest News Contact Us

IJSTR >> Volume 4 - Issue 8, August 2015 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Prediction Of Heart Disease Using Back Propagation MLP Algorithm

[Full Text]



Durairaj M, Revathi V



Index Terms: Minimum ECG, MRI, MLP, Nerual Network.



Abstract: Diagnosing the presence of heart disease is actually tedious process,as it requires depth knowledge and rich experience. In general, the prediction of heart disease lies upon the traditional way of examining medical report such as ECG (The Electrocardiogram), MRI (Magnetic Resonance Imaging), Blood Pressure, Stress tests by a medical practitioner. Now days, a large volume of medical data is available in medical industry and acts as a great source of predicting useful and hidden facts in almost all medical problems. These facts would really in turn, help the practitioners to make accurate predictions. The novel techniques of Artificial Neural Network concepts have also been contributing themselves in yielding highest prediction accuracy over medical data. This paper aims to predict the existence of heart disease using Back Propagation MLP (Multilayer Perceptron) of Artificial Nerual Network. The results are compared with the existing works carried out in the same domain.



[1] Hongmei yan, Yingtao Jiang, Jun Zheng, Chenglin Peng, Qinghui Li,”A Multilayer Perceptron-Based Descision Support System for heart Disease Diagnosis”, 30(2006) 272-281

[2] Miss. Chaitrali S. Dangarw, Dr. Mrs. Sulabha S. Apte,”A Data Mining Approach For Prediction of Heart Disease Using Neural Networks” volume 3, Issue 3, October-december (2012), pp.30-40.

[3] YAN Hongmeil, PENG Chenglin1, DING Xiaojun2, XIAO Shouzhong, “Improving the accuracy of heart disease diagnosis with an augmentes back propagation algorithm”, june 2003.

[4] Roya Asadi, Norwati Mustapha, Nasir Sulaiman, Nematollaah shiri,”New Supervised Multilayer Feed Forward Neural Network Model to Accelerate Classification with High Accuracy”, Vol.33 No.1, pp.163-178

[5] Miss.Manjusha B. Wadhonkar, Prof.P.A. Tijare and Prof. S.N.Saqwalkar,”Classification of Heart disease Datset using Multilayer Feed Forward BackPropogation Algorithm”,Volume 2 issue 4, April 2003.

[6] S.Radhimeenakshi, G.M.Nasira”Prediction of Heart Diease using Nerual Network with Back Propagation” Pages:1166-1169.

[7] Sunila,Prahat,Pandy,Nirmal Godara,”Decision Support for Cardiovascular Heart Disease Diagnosis using Improved Multilayer Perceptron” Computer Applications (0975-8887) Volume 45-no.8, may2012.

[8] Ilias Maglogiannnisa, Euripidis Loukis,Elias Zafiropoulos,Antonis Stas, “Support Vectors Machinebased Identification of Heart Valve Disease using Heart Sounds”, onlinr jaunary 2009.

[9] Todd,R.Reed,Nancy,E.Reed,PeterFrizson,”Heart Sound Analysis for Symptom Detection and Computer-Aided Diagnosis”,2004.

[10] Resul Das, Ibrahim Turkoglu, Bdulkadir Sengur,”Diagnosis of Valvular Heart Disease Through Nerual Networks Ensembles”, 2008.

[11] Harun Ug, Ahmet Arslam, Ridvan Sara, Ibrahim Turkogu,”Detection of Heart Valve Disease by Using Fuzzy Discrete Hidden Markov Model online”, 2008.

[12] Durairaj M, Sivagowry S and Persia A,”An Empircial Study on Applying Data Mining Techniques for the Analysis and Prediction of Heart Disease”,2013.

[13] Durairaj M, Revathi V,”Soft Computing Methodology To Measure Heart Sound-A Survey”,2015.